Forecasting Euro-Yen exchange rate with hidden Markov model and a classification algorithm

The goal of this paper is forecasting the direction (increase or decrease) of EURJPY exchange rate in a day. For this purpose five major indicators are used. Then a hybrid approach using hidden Markov models and CART classification algorithms is developed. Proposed approach is used for forecasting direcation (increase or decrease) of Euro-Yen exchange rate in a day. Also the approach is used for forecasting differnece between intial and maximum (minimum) exchange rates in a day. Result of proposed method is compared with CART and neural network. Comparison shows that the forecasting with proposed method has higher accuracy.

Keywords:

foreign exchange market , forecasting , CART classification algorithm , hidden Markov model , EURJPY exchange rate